Women in Technology: More Diversity Needed in Computer Science Studies

The bi-annual Women in Technology Leadership Round Table was held at UC Berkeley in June, a few months after its organizers, Virginia Smith and Dr. Gitanjali Swamy, issued the report, Women In Tech: Addressing the Root Causes of Attrition. The report, which appeared after the Women in Technology inaugural Round Table in November, provided a comprehensive view of research that has been conducted related to the number of women currently active in technological fields.

Among the facts are these:

The overall number of female undergraduate computer science majors across the country was 18.7% in 2012, much lower than in 1984, when it was 37%, and 1991 when it was 29.6%.

Across STEM fields, computer science and engineering continue to have the lowest level of participation from women, at below 20%.

Computer science and engineering are among the occupations with the lowest percentage of female employees.

One year out of college, women earn only 82% of what men earn for the same role.

At tech giant Google, females account for just 21% of leadership roles. It’s 23% at Facebook, 23% at Yahoo!, and 21% at Twitter.

Ninety percent of VC investments in technology areas like semiconductors, computers, peripherals, electronics, instrumentation, and media/entertainment had a startling 0% of women in leadership.

Just 6% of VC partners are women, a decline from 10% over a decade ago.

The report included findings from the group’s own extensive and ongoing survey of over 200 women in technology and related fields, exploring the reasons for the lack of women in technology.

Its findings included:

First, the good news: Nearly 90% of women indicated that they were very confident in their skills and abilities as they pertain to their career.

Unfortunately, over 90% of women had faced some form of discrimination, with comments noting that it took the form of everything from consistently lower wages to consistently less access to opportunity. Over 40% of women felt that their careers had been negatively impacted by the discrimination.

Mentorship appeared to have the most need for improvement, with more than half of women reporting that they had poor mentorship or none at all.

The statistics highlight an important trend, the report says:

“The main issues seem to be not a lack of willing participants at the inlet of these stages, but instead highlight poor management of women throughout their professional tenure.”

At the spring event, WiT steering committee member and report contributor Janet George, Chief Data Scientist for Big Data at flash memory storage solution vendor SanDisk, led a breakout group to talk about best practices for mentoring, such as helping the mentee to outline a path to success, manage personal balance, and make career choices; for training, such as emphasizing one-on-one coaching for developing the skills needed to move to leadership positions; and, for sponsorship, including cultivating women role models and having sponsors boost a woman’s career by providing access to essential networks, publicizing past achievements, or offering recommendations for future work.

In her role at SanDisk, George builds global core competencies, data platforms, and Advanced Analytics. Before moving there she also worked in executive positions at Apple, Yahoo!, and eBay, and has a particular interest in addressing the deficit of women in top roles in technology – including Data Science. “The numbers are amazingly sad,” she told DATAVERSITY®.

“Fewer and fewer women are picking computer science” to study or take up careers in, perhaps because they’ve lacked mentors or haven’t had exposure to exploring the field to see if they have an interest. She wants to see the numbers change. “When there is a gap you race to fill it, but when you see the numbers going backwards that’s slightly more alarming,” she says.

Step into Computer Science and Step Up Prospects

If it’s possible to get the numbers to spike up, it’s good for women – and good for businesses, too. The report notes, for instance, that research has shown that companies with top quartile gender diversity in top management outperform companies with bottom quartile gender diversity.

As far as individual prospects go, George points out that there is a greater abundance of jobs in the computer science field vs. other STEM fields, such as biology. Not only that, but “computer science is such a flexible course that you can almost transform yourself into any area you want to go into.”

Certainly there are opportunities at the highly technical end of things, with companies still in great need of Data Scientists. According to a recent survey by Crowdflower, 83% of Data Scientists polled feel that there is still a shortage of Data Scientists today. The top ten skills for Data Scientists, it found, are SQL, Hadoop, Python, Java, R, Hive, MapReduce, NoSQL, Pig and SAS, and over half the respondents noted Machine Learning had significant importance for their companies and their departments.

“You could decide to stay deep in computer science as I did for Data Science and Machine Learning,” George says, “but you could also specialize into marketing or product, for example. The important thing is [that by studying computer science], you have the foundation you need as we move into a world where technology is central.”

A Bachelor’s Degree in Computer Science is a good start, but she recommends women look to graduate school, too. And she would like messaging to young people – women and men alike – to emphasize the fact that one needn’t be a math genius to do well in computer science studies. “You don’t have to be good at math naturally. You can be trained to be good at math,” she says.

Bring on the Role Models

When it comes to women role models in the tech industry, they’re out there, she says. In fact, women executives at household name companies – such as Facebook COO Sheryl Sandberg, Yahoo! CEO Marissa Mayer, or HP CEO Meg Whitman – may make headline news more often than many of their male counterparts.

But what might be even more helpful to young women is having greater exposure to more “everyday” women tech executives in the workplace – people they can more readily relate to, she says. She gives herself as an example: “I’m a regular employee in a regular company,” she says, and younger women may well find George and her peers in similar positions as more readily accessible to support them as mentors and sponsors.

Of course, reaching women when they are still students is a first step, as they make their decisions about what to major in for undergraduate or graduate courses. Having outreach to them and being vocal about real-world computer science success stories is one important tactic. But she wants to dive deeper. “What are the signals that go into their decision-making? We have to crack that to change the equation,” she says.

George has been putting her expertise in Data Science to work to try to start to answer that question. “We have a lot of data through social media, surveys, etc.,” she says, and “we are analyzing it.” The questions then will be, given the data, how to help young women become more informed about their choices, how to map what is learned about their interests to how those interests intersect with computer science? What skills and talents do they have that can be harnessed in that direction? What are the best ways to help them understand what a career looks like and how it can be fun for them?

“That’s the challenge,” she says. “We don’t want women with the capabilities [to succeed in computer science] to go in a different direction.”

About the author

Jennifer Zaino is a New York-based freelance writer specializing in business and technology journalism. She has been an executive editor at leading technology publications, including InformationWeek, where she spearheaded an award-winning news section, and Network Computing, where she helped develop online content strategies including review exclusives and analyst reports. Her freelance credentials include being a regular contributor of original content to The Semantic Web Blog; acting as a contributing writer to RFID Journal; and serving as executive editor at the Smart Architect Smart Enterprise Exchange group. Her work also has appeared in publications and on web sites including EdTech (K-12 and Higher Ed), Ingram Micro Channel Advisor, The CMO Site, and Federal Computer Week.